Can a Greenhouse Be Established on Mars?
Bibliographic record
Abstract
This study investigates the potential of establishing a greenhouse on Mars. In order to sustain a greenhouse on Mars, the variables that must be considered are water, soil, atmosphere, light, temperature, design, and plants. Water is present on Mars in the form of ice in frozen soil. Water extraction can be achieved by heating, microwaves, or humidifier type devices. The water that is extracted is highly salty. However, ion exchange, reverse osmosis, or biological treatments can be used to treat the water. By using an underground irrigation system, this water can be applied directly to plant roots. Soil is readily available on Mars, and, with the exception of reactive nitrogen, this soil contains the nutrients required for plant growth. Nitrogen fixers, such as Cyanobacteria, can convert nitrogen from the atmosphere into reactive nitrogen. This reactive nitrogen can be directly applied to the plants. The atmosphere of Mars contains 95.32% Carbon Dioxide, 2.7% Nitrogen, 1.6% Argon, 0.13% Oxygen and 0.08% Carbon Monoxide. Mars' atmosphere is very thin so it has difficulty capturing solar energy, but this difficulty can be overcome by creating more greenhouse gases on the planet via thawing the poles using orbital mirrors, creating greenhouse gas factories, or smashing ammonia heavy asteroids into the planet. Artificial light can also be used to supply solar energy. Temperatures on Mars fluctuate between 35 to - 90 degrees Celsius, depending on the season. To overcome these large fluctuations, a radioisotope heater can be used to maintain temperatures within the greenhouse between the ideal 0 - 40 degrees Celsius. Robots or humans can set up and maintain the greenhouse. Plants that are to be grown in a greenhouse on Mars must be able to sustain human life by providing the proper nutrients. These include soybeans, spinach, mushrooms, wheat, Spirulina platensis (cyanobacteria supplementation) and seaweed. Ultimately, this research suggests that building and maintaining a Martian greenhouse may be feasible in the future by utilizing a number of techniques and technologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".